Governments can use artificial intelligence (AI) to design better policies and make better and more targeted decisions, enhance communication and engagement with citizens, and improve the speed and quality of public services. The Latin America and the Caribbean (LAC) region is seeking to leverage the immense potential of AI to promote the digital transformation of the public sector. The OECD, in collaboration with CAF, Development Bank of Latin America, prepared this report to help national governments in the LAC region understand the current regional baseline of activities and capacities for AI in the public sector; to identify specific approaches and actions they can take to enhance their ability to use this emerging technology for efficient, effective and responsive governments; and to collaborate across borders in pursuit of a regional vision for AI in the public sector. This report incorporates a stocktaking of each country’s strategies and commitments around AI in the public sector, including their alignment with the OECD AI Principles. It also includes an analysis of efforts to build key governance capacities and put in place critical enablers for AI in the public sector. It concludes with a series of recommendations for governments in the LAC region.

This report compiles comparable tax revenue statistics over the period 1990-2020 for 27 Latin American and Caribbean economies. Based on the OECD Revenue Statistics database, it applies the OECD methodology to countries in Latin America and the Caribbean to enable comparison of tax levels and tax structures on a consistent basis, both among the economies of the region and with other economies. This publication is jointly undertaken by the OECD Centre for Tax Policy and Administration, the OECD Development Centre, the Inter-American Center of Tax Administrations (CIAT), the Economic Commission for Latin America and the Caribbean (ECLAC) and the Inter-American Development Bank (IDB).

This report compiles comparable tax revenue statistics over the period 1990-2019 for 27 Latin American and Caribbean economies. Based on the OECD Revenue Statistics database, it applies the OECD methodology to countries in Latin America and the Caribbean to enable comparison of tax levels and tax structures on a consistent basis, both among the economies of the region and with other economies. This publication is jointly undertaken by the OECD Centre for Tax Policy and Administration, the OECD Development Centre, the Inter-American Center of Tax Administrations (CIAT), the Economic Commission for Latin America and the Caribbean (ECLAC) and the Inter-American Development Bank (IDB). The 2021 edition is produced with the support of the EU Regional Facility for Development in Transition for Latin America and the Caribbean, which results from joint work led by the European Union, the OECD and its Development Centre, and ECLAC.

This report compiles comparable tax revenue statistics over the period 1990-2018 for 26 Latin American and Caribbean economies. Based on the OECD Revenue Statistics database, it applies the OECD methodology to countries in Latin America and the Caribbean to enable comparison of tax levels and tax structures on a consistent basis, both among the economies of the region and with other economies. This publication is jointly undertaken by the OECD Centre for Tax Policy and Administration, the OECD Development Centre, the Inter-American Center of Tax Administrations (CIAT), the Economic Commission for Latin America and the Caribbean (ECLAC) and the Inter-American Development Bank (IDB). The 2020 edition is produced with the support of the EU Regional Facility for Development in Transition for Latin America and the Caribbean, which results from joint work led by the European Union, the OECD and its Development Centre, and ECLAC.

Small island developing states (SIDS) have been acutely affected by the economic impacts of the COVID-19 pandemic. This paper takes a broader perspective to explore how the revenue effects of this crisis in SIDS are connected to their unique financing and development challenges. It also suggests how SIDS governments and development co-operation providers can better partner together to strengthen mobilisation of domestic revenues – in particular tax revenues – in the recovery post-COVID-19.

This dataset includes pension funds statistics with OECD classifications by type of pension plans and by type of pension funds. All types of plans are included (occupational and personal, mandatory and voluntary). The OECD classification considers both funded and book reserved pension plans that are workplace-based (occupational pension plans) or accessed directly in retail markets (personal pension plans). Both mandatory and voluntary arrangements are included. The data includes plans where benefits are paid by a private sector entity (classified as private pension plans by the OECD) as well as those paid by a funded public sector entity. Data are presented in various measures depending on the variable: millions of national currency, millions of USD, thousands or unit.

This dataset includes pension funds statistics with OECD classifications by type of pension plans and by type of pension funds. All types of plans are included (occupational and personal, mandatory and voluntary). The OECD classification considers both funded and book reserved pension plans that are workplace-based (occupational pension plans) or accessed directly in retail markets (personal pension plans). Both mandatory and voluntary arrangements are included. The data includes plans where benefits are paid by a private sector entity (classified as private pension plans by the OECD) as well as those paid by a funded public sector entity. Data are presented in various measures depending on the variable: millions of national currency, millions of USD, thousands or unit.

This dataset includes pension funds statistics with OECD classifications by type of pension plans and by type of pension funds. All types of plans are included (occupational and personal, mandatory and voluntary). The OECD classification considers both funded and book reserved pension plans that are workplace-based (occupational pension plans) or accessed directly in retail markets (personal pension plans). Both mandatory and voluntary arrangements are included. The data includes plans where benefits are paid by a private sector entity (classified as private pension plans by the OECD) as well as those paid by a funded public sector entity. Data are presented in various measures depending on the variable: millions of national currency, millions of USD, thousands or unit.

This dataset comprises statistics pertaining to pensions indicators.It includes indicators such as occupational pension funds’asset as a % of GDP, personal pension funds’ asset as a % of GDP, DC pension plans’assets as a % of total assets. Pension fund and plan types are classified according to the OECD classification. Three dimensions cover this classification: pension plan type, definition type and contract type.

This dataset comprises statistics pertaining to pensions indicators.It includes indicators such as occupational pension funds’asset as a % of GDP, personal pension funds’ asset as a % of GDP, DC pension plans’assets as a % of total assets. Pension fund and plan types are classified according to the OECD classification. Three dimensions cover this classification: pension plan type, definition type and contract type.